A test of highly optimized tolerance reveals fragile cell-cycle mechanisms are molecular targets in clinical cancer trials

Robustness, a long-recognized property of living systems, allows function in the face of uncertainty while fragility, i.e., extreme sensitivity, can potentially lead to catastrophic failure following seemingly innocuous perturbations. Carlson and Doyle hypothesized that highly-evolved networks, e.g....

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Veröffentlicht in:PloS one 2008-04, Vol.3 (4), p.e2016-e2016
Hauptverfasser: Nayak, Satyaprakash, Salim, Saniya, Luan, Deyan, Zai, Michael, Varner, Jeffrey D
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Salim, Saniya
Luan, Deyan
Zai, Michael
Varner, Jeffrey D
description Robustness, a long-recognized property of living systems, allows function in the face of uncertainty while fragility, i.e., extreme sensitivity, can potentially lead to catastrophic failure following seemingly innocuous perturbations. Carlson and Doyle hypothesized that highly-evolved networks, e.g., those involved in cell-cycle regulation, can be resistant to some perturbations while highly sensitive to others. The "robust yet fragile" duality of networks has been termed Highly Optimized Tolerance (HOT) and has been the basis of new lines of inquiry in computational and experimental biology. In this study, we tested the working hypothesis that cell-cycle control architectures obey the HOT paradigm. Three cell-cycle models were analyzed using monte-carlo sensitivity analysis. Overall state sensitivity coefficients, which quantify the robustness or fragility of a given mechanism, were calculated using a monte-carlo strategy with three different numerical techniques along with multiple parameter perturbation strategies to control for possible numerical and sampling artifacts. Approximately 65% of the mechanisms in the G1/S restriction point were responsible for 95% of the sensitivity, conversely, the G2-DNA damage checkpoint showed a much stronger dependence on a few mechanisms; approximately 32% or 13 of 40 mechanisms accounted for 95% of the sensitivity. Our analysis predicted that CDC25 and cyclin E mechanisms were strongly implicated in G1/S malfunctions, while fragility in the G2/M checkpoint was predicted to be associated with the regulation of the cyclin B-CDK1 complex. Analysis of a third model containing both G1/S and G2/M checkpoint logic, predicted in addition to mechanisms already mentioned, that translation and programmed proteolysis were also key fragile subsystems. Comparison of the predicted fragile mechanisms with literature and current preclinical and clinical trials suggested a strong correlation between efficacy and fragility. Thus, when taken together, these results support the working hypothesis that cell-cycle control architectures are HOT networks and establish the mathematical estimation and subsequent therapeutic exploitation of fragile mechanisms as a novel strategy for anti-cancer lead generation.
doi_str_mv 10.1371/journal.pone.0002016
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subjects Breast cancer
Cancer
Catastrophic failure analysis
Cell Biology
Cell Biology/Cell Growth and Division
Cell Biology/Cell Signaling
Cell culture
Cell Cycle
Cell division
Cell growth
Circadian rhythm
Clinical trials
Clinical Trials as Topic
Clustering
Computational Biology
Computational Biology/Signaling Networks
Computational Biology/Systems Biology
Computer applications
Computer simulation
Control
Cyclin B
Cyclin E
Deoxyribonucleic acid
DNA
DNA Damage
Engineering
Experimental research
Exploitation
Face recognition
Fragility
G1 Phase
Genes
Humans
Hypotheses
Malfunctions
Mathematical models
Medical research
Models, Biological
Monte Carlo simulation
Neoplasms - epidemiology
Neoplasms - pathology
Networks
Ordinary differential equations
Perturbation methods
Proteins
Proteolysis
Robustness (mathematics)
S Phase
Sensitivity analysis
Statistics, Nonparametric
Tumors
title A test of highly optimized tolerance reveals fragile cell-cycle mechanisms are molecular targets in clinical cancer trials
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